Do Calculated Conflicts in Microsimulation Model Predict Number of Crashes?

Dijkstra, A; Marchesini, Paula; Bijleveld, F D; Kars, Vincent; Drolenga, Hans; Maarseveen, Martin van

doi:10.3141/2147-13

Cited by 68 publications

(29 citation statements)

References 5 publications

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“…It is generally considered that a TTC, equal to or less than 1.5 seconds, would result in an unsafe situation [26,36,37]. This threshold of 1.5 seconds is therefore applied for potential conflicts involving HVs (HV-HV and HV-AV).…”

Section: Surrogate Safety Measuresmentioning

confidence: 99%

Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

Morando

Tian

Truong

et al. 2018

Journal of Advanced Transportation

187

114

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Autonomous vehicle (AV) technology has advanced rapidly in recent years with some automated features already available in vehicles on the market. AVs are expected to reduce traffic crashes as the majority of crashes are related to driver errors, fatigue, alcohol, or drugs. However, very little research has been conducted to estimate the safety impact of AVs. This paper aims to investigate the safety impacts of AVs using a simulation-based surrogate safety measure approach. To this end, safety impacts are explored through the number of conflicts extracted from the VISSIM traffic microsimulator using the Surrogate Safety Assessment Model (SSAM). Behaviours of human-driven vehicles (HVs) and AVs (level 4 automation) are modelled within the VISSIM's carfollowing model. The safety investigation is conducted for two case studies, that is, a signalised intersection and a roundabout, under various AV penetration rates. Results suggest that AVs improve safety significantly with high penetration rates, even when they travel with shorter headways to improve road capacity and reduce delay. For the signalised intersection, AVs reduce the number of conflicts by 20% to 65% with the AV penetration rates of between 50% and 100% (statistically significant at < 0.05). For the roundabout, the number of conflicts is reduced by 29% to 64% with the 100% AV penetration rate (statistically significant at < 0.05).

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Section: Surrogate Safety Measuresmentioning

confidence: 99%

Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

Morando

Tian

Truong

et al. 2018

Journal of Advanced Transportation

187

114

View full text Add to dashboard Cite

show abstract

“…Dijkstra et al . used PARAMICS to model the traffic of 569 junctions in the Netherlands. The relationship between observed crashes and simulated conflicts was assessed by using generalized linear models.…”

Section: Previous Workmentioning

confidence: 99%

“…The relationship between observed crashes and simulated conflicts was assessed by using generalized linear models. It was found that the number of conflicts at junctions and the number of passing motor vehicles are statistically related to the number of observed crashes .…”

Section: Previous Workmentioning

confidence: 99%

A comparison between PARAMICS and VISSIM in estimating automated field‐measured traffic conflicts at signalized intersections

Essa

Sayed

2016

J of Advced Transportation

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SUMMARYThe main objective of this study is to investigate the relationship between field-measured conflicts and simulated conflicts estimated from microsimulation model (PARAMICS) using the surrogate safety assessment model. An urban signalized intersection was selected for analysis. Automated video-based computer vision techniques were used to identify field conflicts. The applicability of a two-step model calibration procedure applied to VISSIM in a recent study was investigated using PARAMICS. In the first calibration step, the PARAMICS model was calibrated to ensure that the simulation gives reasonable results of average delay times. The second calibration step used a genetic algorithm procedure to calibrate PARAMICS parameters to enhance the correlation between simulated and field-measured conflicts. Finally, the results obtained from PARAMICS were compared with results obtained from VISSIM. The comparison included three aspects: (i) the car-following model and safety-related parameters; (ii) the correlation between simulated and field-measured conflicts; and (iii) the conflict spatial distributions. The results show that the default simulation model parameters give poor correlation with the field-measured data, and therefore, using simulation models without a proper calibration should be avoided. Overall, good correlation between field-measured and simulated conflicts was obtained after calibration for both models, especially at higher timeto-collision (TTC) values. At TTC threshold of 1.5 s, PARAMICS overestimates the number of conflicts and VISSIM underestimates it. Both models overestimated the number of conflicts at TTC threshold of 3.00 s. There were major differences between field-measured and simulated conflicts spatial distributions for both simulation models. This indicates that despite the good correlation obtained from the calibration process, both PARAMICS and VISSIM do not capture the actual conflict occurrence mechanism. Copyright

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“…In another study, Dijkstra et al, (2010) intersections was rear-end conflicts and crashes. However, significant differences were found between the number of lateral crashes 1 and the number of lateral conflicts at signalized intersections.…”

Section: Microsimulation Studies Based On Ttc and Petmentioning

confidence: 95%

Investigation of Using Microscopic Traffic Simulation Tools to Predict Traffic Conflicts Between Right-Turning Vehicles and Through Cyclists at Signalized Intersections

AlRajie¹

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Researchers have been questioning if traffic microsimulation tools can be used for road safety evaluations. This thesis examines if these tools have the potential to predict conflicts between right-turning vehicles and through cyclists at signalized intersections.Moreover, this thesis evaluates if calibrating these models to describe the driving behaviour at signalized intersections significantly improves the conflicts' prediction. It was found that VISSIM has the potential to predict traffic conflicts of interest. In particular, a moderate correlation was found between real conflicts and simulated conflicts of the default models ( = 0.525). Calibrating the model for travel time improved the correlation between real conflicts and simulated conflicts ( = 0.618). However, a one-way ANOVA test indicated that the improvement caused by travel time calibration was not significant. It was also found that VISSIM's prediction accuracy is expected to decrease as either the cyclists' volume or the product of cyclists' volume and right-turning vehicles' volume increase.iii

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Do Calculated Conflicts in Microsimulation Model Predict Number of Crashes?

Cited by 68 publications

References 5 publications

Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

A comparison between PARAMICS and VISSIM in estimating automated field‐measured traffic conflicts at signalized intersections

Investigation of Using Microscopic Traffic Simulation Tools to Predict Traffic Conflicts Between Right-Turning Vehicles and Through Cyclists at Signalized Intersections

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